CNNs, recurrent nets, autoencoders, GANs, and skip connections
How CNNs see and understand images
How RNNs read and understand sequences
Gates and memory cells for long sequences
From compression to generation — standard and variational autoencoders
Two networks competing to create
Residual learning and why deeper networks work